Download on GitHub This python script adds information on physical disks to a Microsoft Access database. The information is automatically retrieved from hddfaqs.com, using the model number of the disks scanned by the user.

The database is stored in .\DATABASE\Inventory.accdb

To use the script you have to install :

Microsoft Access
Python

The python architecture must be the same as that of Microsoft Access.

Python x64 <--> MS access x64
Python x86 <--> MS access x86

Microsoft Access database structure

TABLE NAME : DRIVES

Column	Type
ID_Drives	AutoIncrement
Model_Number	ShortText
Brand	ShortText
Storage_in_GB	Number
Size	ShortText
Serial_Number	LongText
Cache	ShortText
Date	ShortText
Country	ShortText
Tested	Yes/No
Interface	ShortText
Working	Yes/No
Label_notes	LongText
Miscelanious	LongText
Location	ShortText

sql

CREATE TABLE DRIVES (
    ID_Drives AUTOINCREMENT PRIMARY KEY,
    Model_Number SHORT TEXT,
    Brand SHORT TEXT,
    Storage_in_GB NUMBER,
    Size SHORT TEXT,
    Serial_Number LONG TEXT,
    Cache SHORT TEXT,
    Date SHORT TEXT,
    Country SHORT TEXT,
    Tested YESNO,
    Interface SHORT TEXT,
    Working YESNO,
    Label_notes LONG TEXT,
    Miscelanious LONG TEXT,
    Location SHORT TEXT
);

Libraries :

python

import requests
from bs4 import BeautifulSoup
import re
import pyodbc

Library	Usage
Requests	to fetch the datas from hddfaqs.com
BeautifulSoup	to parse the HTML page
re	to search and manipulate strings
pyodbc	for connection to the Microsoft Access database

You can install the libraries using the requirements.txt

bash

pip install -r requirements.txt

Script logic

For the moment, hddfaqs doesn't offer an API for data retrieval. The script uses a WebScrapping technique, which consists in extracting the HTML elements of a page, and then retrieving the raw values.

To find the right drive, the script uses the search system to find the first result, then visits the new page for the data.

Try to connect to the database using the pyodbc library

python

try:
   conn = pyodbc.connect(r'DRIVER={Microsoft Access Driver (*.mdb, *.accdb)};DBQ=.\DATABASE\Inventory.accdb;')
   print(f"{color.BOLD}{color.GREEN}Connected To Database {color.END} {color.END}")
   cursor = conn.cursor()
except pyodbc.Error as e:
   print("Error in Connection", e)

Main loop

python

while True:
    #### ASK THE USER TO SCAN A DRIVE ####
    model_number = input(f'{color.BOLD}Scan the model number>> {color.END}')

Now the URL is: https://hddfaqs.com/?s= + model_number

Then, the script tries out the entire script in safe mode. If there's an error somewhere, it displays the error but doesn't stop the script.

python

try:
    #### SCRIPT ####
except Exception as e:
    print("Error: ", e)

Still in safe mode, the script is using the requests lib to fetch the URL. In the headers, we specify a user-agent to make the platform believe that we are an ordinary user.

python

req = requests.get(url, headers={'User-Agent': 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36'})

In the result, the script attempts to obtain the first element. If it fails to do so, this means that the disk is not in the database, which interrupts the loop.

python

try:
    url = soup.find('article').find_all('a')[0].get("href")
except:
    print(f"{color.BOLD}{color.RED}This disk doesn't exist {color.END}{color.END}")
    continue

If successful, the URL has been modified by the url of the first element. The script retrieves the new page.

Retrieving disk information :

CAPACITY :

python

# Finds the li element in article with content that starts with "Capacity: "
capacity_text = str(soup.find("article").find("li", string=lambda text: text and text.startswith('Capacity: ')).text)
# Gets the value
capacity = capacity_text.split()[1:2][0]
# Gets the unit (TB, GB, MB)
capacity_unit = str(soup.find("article").find("li", string=lambda text: text and text.startswith('Capacity: ')).text).split()[2:3][0]

Sometimes on hddfaqs it can't work because on some pages the text is written with Ex: <li><strong>Storage Capacity: </strong>128 GB</li> and not Ex: <li>Capacity: 128GB</li> so the script can't read the value with this method. That's why it uses safe mode for this, because if it doesn't work, we try the second method, and if it still doesn't work, error...

so here is the second method :

python

# Finds the element "Storage Capacity".
storage_capacity_element = soup.find("strong", string=lambda text: text and text.startswith('Storage Capacity: '))
# Selects the next element
capacity_text = storage_capacity_element.find_next('li')
# Select the previous one
capacity_text = capacity_text.find_previous('li').text.split()[-1]

# Parse the content (Digits=Drive_Capacity | alpha=Drive_Unit)
capacity = "".join(filter(str.isdigit, capacity_text))
capacity_unit = "".join(filter(str.isalpha, capacity_text))

The script needs the capacity unit beacause on some drives the values can switch between GB, TB, MB. And in the database we only want GB, so we have to convert the value :

python

# Switch statement
match capacity_unit:
    # If capacity unit is TB so we multiply the value by 1000
    case "TB":
        capacity = int(capacity)*1000
    # If capacity unit is MB so we divide the value by 1000
    case "MB":
        capacity = int(capacity)/1000
    # Else it's already in GB we can ignore it
    case _:
        pass

BRAND :

For the brand this is the same way, first it tries to find an element like <li>Manufacturer: Toshiba</li>

python

manufacturer = str(soup.find("article").find("li", string=lambda text: text and text.startswith('Manufacturer: ')).text).split()[1:][0]

If it can't it tries to find a <strong> element, select the next one, then the previous one.

python

manu_element = soup.find("strong", string=lambda text: text and text.startswith('Manufacturer: '))
try:
    manufacturer = manu_element.find_next('li')
    manufacturer = manufacturer.find_previous('li').text.split()[-1]
except:
    manufacturer = manu_element.find_previous('li')
    manufacturer = manufacturer.find_next('li').text.split()[-1]

SIZE :

Same method as BRAND

CACHE :

Finding the disk cache is a different method. The script selects the disk description ".desc1" because the cache is somewhere in the description. It therefore uses the re library to find the text "MB Cache". We then analyze the value just before it. If it finds something, we have the cache, otherwise the cache won't be in the database.

python

desc = str(soup.select_one('.des1'))
pattern = r"(\d+)MB Cache"
match = re.search(pattern, desc)
try:
    cache = match.group(1)
except:
    cache = ""

INTERFACE :

Finding the interface is the same method as BRAND and CACHE.

Some results have to be converted.

python

match interface:
    # If interface is "Serial-ATA" it will be "SATA"
    case "Serial-ATA":
        interface = "SATA"
    # If interface is "Ultra-ATA" it will be "IDE"
    case "Ultra-ATA":
        interface = "IDE"
    # If interface is "ATA" it will be "IDE"
    case "ATA":
        interface = "IDE"
    # Else it skips
    case _:
        pass

The script can't find certain information on its own using hddfaqs, such as serial number or date, country, location. It therefore asks the user to provide this information using the :

python

serial_number = input(f'{color.BOLD}{color.YELLOW}Scan the serial number (Enter if no)>> {color.END}{color.END}')
date = str(input(f'{color.BOLD}{color.YELLOW}Enter the date (Enter if no)>> {color.END}{color.END}'))
country = input(f'{color.BOLD}{color.YELLOW}Enter the country (Enter if no)>> {color.END}{color.END}')
location = input(f'{color.BOLD}{color.YELLOW}Enter the location (Enter if no)>> {color.END}{color.END}')

Finishing :

Finally, it displays all the drive information to the user. If all values are correct, it adds the drive to the database. If not, it requests the correct capacity and manufacturer.

Adding the drive to the database:

SQL command :

sql

INSERT INTO DRIVES(Model_Number, Brand, Storage_in_GB, Size, Serial_Number, Cache, [Date], Country, Interface, Type, Location) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)

Credits

Made by h0ag for Computer Doctor

HWIKI

Microsoft Access Disk Inventory

Microsoft Access database structure

Libraries :

You can install the libraries using the requirements.txt

Script logic

Try to connect to the database using the pyodbc library

Main loop

Finishing :

Credits